You can download the paper at F1000Research and cite the paper:

• Yang Z, Pandey P, Marjoram P and Siegmund KD. iMutSig: a web application to identify the most similar mutational signature using shiny [version 2; peer review: 2 approved]. F1000Research 2020, 9:586 (https://doi.org/10.12688/f1000research.24435.2)

This Shiny app is hosted at shinyapps.io where you can access using the link https://zhiyang.shinyapps.io/imutsig/.

If you'd like to use this Shiny app locally, please type the following command in your RStudio.

git clone https://github.com/USCbiostats/iMutSig.git

To run the Shiny app, you need to install the following packages. If you run into any issues while installing pmsignature, please refer to its GitHub page for more details https://github.com/friend1ws/pmsignature.

packages <- c("shinyjs", "shinydashboard", "shiny", "dplyr", 
              "DT", "corrplot", "stringr", "devtools")
if (length(setdiff(packages, rownames(installed.packages()))) > 0) {
  install.packages(setdiff(packages, rownames(installed.packages())))  
}

if (!("d3heatmap" %in% rownames(installed.packages()))){
  devtools::install_github("rstudio/d3heatmap")
}

if (!("pmsignature" %in% rownames(installed.packages()))){
  devtools::install_github("friend1ws/pmsignature", ref = "devel")
}

if (!("decompTumor2Sig" %in% rownames(installed.packages()))){
  devtools::install_github("zhiiiyang/decompTumor2Sig")
}

By clicking the Run App button in either ui.R or server.R script, a Shiny app will run locally. Or you can simply enter runApp() in the console.

Please open an issue at https://github.com/USCbiostats/iMutSig/issues if you run into any issues or would like to add a new feature. Thank you!

This work was supported by NCI grant numbers 5P30 CA014089 and P01 CA196569.